Method and Apparatus for Optimizing Queries in a Logically Partitioned Computer System

ABSTRACT

A database query optimizer for a computer system having dynamically configurable logical partitions generates an optimized query strategy which is dependent on a logical partition configuration. When the query is executed, the configuration of the logical partition in which the query is executed is compared to the logical partition configuration for which the query was optimized. If the configurations are different, a new query can be automatically generated. Optimizing database queries to the current system configuration of a dynamic, logically partitioned system potentially offers greater efficiency in the execution of database queries for complex, logically partitioned systems.

CROSS REFERENCE TO RELATED APPLICATIONS

This is a continuation of pending U.S. patent application Ser. No.11/117,617, filed Apr. 28, 2005, entitled “Method and Apparatus forOptimizing Queries in a Logically Partitioned Computer System”, which isa continuation of U.S. patent application Ser. No. 10/001,667, filedOct. 25, 2001, entitled “Method and Apparatus for Optimizing Queries ina Logically Partitioned Computer System”, now issued as U.S. Pat. No.6,931,395, both of which are herein incorporated by reference. Thisapplication is also related to pending U.S. patent application Ser. No.11/931,900, filed Oct. 31, 2007, entitled “Method and Apparatus forOptimizing Queries in a Logically Partitioned Computer System”.

FIELD OF THE INVENTION

The present invention relates generally to digital data processing, andmore particularly to the generation of database queries in a digitalcomputer system.

BACKGROUND OF THE INVENTION

A modern computer system typically comprises a central processing unit(CPU) and supporting hardware necessary to store, retrieve and transferinformation, such as communications busses and memory. It also includeshardware necessary to communicate with the outside world, such asinput/output controllers or storage controllers, and devices attachedthereto such as keyboards, monitors, tape drives, disk drives,communication lines coupled to a network, etc. The CPU is the heart ofthe system. It executes the instructions which comprise a computerprogram and directs the operation of the other system components.

From the standpoint of the computer's hardware, most systems operate infundamentally the same manner. Processors are capable of performing alimited set of very simple operations, such as arithmetic, logicalcomparisons, and movement of data from one location to another. But eachoperation is performed very quickly. Programs which direct a computer toperform massive numbers of these simple operations give the illusionthat the computer is doing something sophisticated. What is perceived bythe user as a new or improved capability of a computer system is madepossible by performing essentially the same set of very simpleoperations, but doing it much faster. Therefore continuing improvementsto computer systems require that these systems be made ever faster.

The overall speed of a computer system (also called the “throughput”)may be crudely measured as the number of operations performed per unitof time. Many improvements have been made and continue to be made toincrease the speed of individual computer processors. However, there arecertain limits to processor clock speed, number of circuits on a chip,and so forth which limit the overall throughput of a single processor.To support increasing demand for computing resource, it has becomecommon in many large systems to employ multiple processors as a means offurther increasing the throughput of the system. Additionally, suchlarge systems may have multiple caches, buses, I/O drivers, storagedevices and so forth.

The proliferation of system components introduces various architecturalissues involved in managing these resources. For example, multipleprocessors typically share the same main memory (although each processormay have its own cache). If two processors have the capability toconcurrently read and update the same data, there must be mechanisms toassure that each processor has authority to access the data, and thatthe resulting data is not gibberish. Another architectural issue is theallocation of processing resources to different tasks in an efficientand “fair” manner, i.e., one which allows all tasks to obtain reasonableaccess to system resources. There are further architectural issues,which need not be enumerated in great detail here.

One recent development in response to this increased system complexityis to support logical partitioning of the various resources of a largecomputer system. Conceptually, logical partitioning means that multiplediscrete partitions are established, and the system resources of certaintypes are assigned to respective partitions. Specifically, processorresources of a multi-processor system may be partitioned by assigningdifferent processors to different partitions, by sharing processorsamong some partitions and not others, by specifying the amount ofprocessing resource measure available to each partition which is sharinga set of processors, and so forth. Each task executes within a logicalpartition, meaning that it can use only the resources assigned to thatpartition, and not resources assigned to other partitions.

Logical partitions are generally defined and allocated by a systemadministrator or user with similar authority. I.e., the allocation isperformed by issuing commands to appropriate management softwareresident on the system, rather than by physical reconfiguration ofhardware components. It is expected, and indeed one of the benefits oflogical partitioning is, that the authorized user can re-allocate systemresources in response to changing needs or improved understanding ofsystem performance. Some logical partitioning systems support dynamicpartitioning, i.e., the changing of certain resource definitionparameters while the system is operational, without the need to shutdown the system and re-initialize it.

Complex systems may be used to support a variety of applications, butone common use is the maintenance of large databases, from whichinformation may be obtained. Large databases usually support some formof database query for obtaining information which is extracted fromselected database fields and records. Such queries can consumesignificant system resources, particularly processor resources.

A query involves retrieving and examining records in a databaseaccording to some search strategy. Not all strategies are equal. Variousfactors may affect the choice of optimum search strategy. To supportdatabase queries, some large database applications have query optimizerswhich construct search strategies. An optimizer is an applicationprogram which is intended to construct a near optimal search strategyfor a given set of search parameters, according to known characteristicsof the database, the system on which the search strategy will beexecuted, and/or and optional user specified optimization goals. Often,a query (search strategy) constructed by a query optimizer can be savedand re-used again and again.

In constructing a search strategy, some query optimizers consider theconfiguration of a computer system. I.e., depending on the systemresources, it may be possible to execute different parts of the querysimultaneously on different processors. For example, one processor mayfind all records wherein a field X matches parameter x₀, while anotherprocessor concurrently finds all records wherein a field Y matchesparameter y₀. The two lists of records found by the two processors maysubsequently be combined by intersection, union or other more complexoperations. In this case, it is likely that the availability of twoprocessors will reduce the total time required to perform the query.

Where a system is logically partitioned, the query executes in one ofthe logical partitions. In the case of dynamically defined logicalpartitions, it is possible that the parameters of the logical partitionin which the query executes will change. A query which is optimized by aquery optimizer and executed after a substantial time lag (e.g., isdesigned to be re-used periodically) might therefore have been generatedunder system configuration assumptions which are no longer true. A needtherefore exists, not necessarily recognized, to as sure that querystrategies accurately reflect the current system configuration underwhich they are to be executed.

SUMMARY OF THE INVENTION

A query optimizer for database queries in a computer system havingdynamically configurable logical partitions generates an optimized querystrategy which is dependent on a logical partition configuration. Whenthe query is executed, the configuration of the logical partition inwhich the query is executed is compared to the logical partitionconfiguration for which the query was optimized. If the configurationsare different, a new query can be automatically generated.

In the preferred embodiment, the system is configured as a plurality oflogical partitions, each partition having an assigned set of physicalprocessors (which may be shared with one or more other partitions), anassigned processor resource measure (i.e., a processor resource measurein units of equivalent physical processors) and an assigned number ofvirtual processors. In a rough sense, each partition behaves as if itcontains as many processors as the assigned number of virtualprocessors, each such processor having an appropriate fraction of theprocessing capacity of a physical processor. The set of physicalprocessors, the processor resource measure, and the number of virtualprocessors assigned to a logical partition may be dynamically alteredduring system operation.

Preferably, a database query optimizer considers the logicalconfiguration of the logical partition to which it is assigned whenoptimizing database queries. In particular, the number of virtualprocessors is used to optimize the query. Since the logicalconfiguration is subject to dynamic changes, the query optimizerdetermines current configuration when optimizing the query.

Preferably, the query optimizer may save a query as a persistent objectfor later use. The system configuration assumptions used for optimizingthe query are saved in the query object, in particular, the number ofvirtual processors of the partition. This information is compared tocurrent system data when the query is later called for execution.

Preferably, the user may optionally disable re-optimization of a querynotwithstanding a change in the configuration of logical partitions.

Optimizing database queries to the current system configuration of adynamic, logically partitioned system potentially offers greaterefficiency in the execution of database queries for complex, logicallypartitioned systems.

The details of the present invention, both as to its structure andoperation, can best be understood in reference to the accompanyingdrawings, in which like reference numerals refer to like parts, and inwhich:

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a high-level block diagram of the major hardware components ofa logically partitioned computer system having multiple CPUs, accordingto the preferred embodiment of the invention described herein.

FIG. 2 is a conceptual illustration showing the existence of logicalpartitions at different hardware and software levels of abstraction in acomputer system, according to the preferred embodiment.

FIG. 3 shows an example logical partitioning processor allocation for asystem having eight physical processors, according to the preferredembodiment.

FIG. 4 illustrates at a high level various user applications and data ina logical partition of a computer system, according to the preferredembodiment.

FIG. 5 is a flow diagram illustrating at a high level the process ofgenerating an optimized query strategy object, according to thepreferred embodiment.

FIG. 6 is a flow diagram illustrating at a high level the process ofexecuting a previously created and optimized query strategy, accordingto the preferred embodiment.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Logical PartitioningOverview

Logical partitioning is a technique for dividing a single large computersystem into multiple partitions, each of which behaves in some respectsas a separate computer system. Certain resources of the system may beallocated into discrete sets, such that there is no sharing of a singleresource among different partitions, while other resources may be sharedon a time interleaved or other basis. Examples of resources which may bepartitioned are central processors, main memory, I/O processors andadapters, and I/O devices. Each user task executing in a logicallypartitioned computer system is assigned to one of the logical partitions(“executes in the partition”), meaning that it can use only the systemresources assigned to that partition, and not resources assigned toother partitions.

Logical partitioning is indeed logical rather than physical. A generalpurpose computer typically has physical data connections such as busesrunning between a resource in one partition and one in a differentpartition, and from a physical configuration standpoint, there istypically no distinction made with regard to logical partitions.Generally, logical partitioning is enforced by low-level encoded data,which is referred to as “licensed internal code”, although there may bea certain amount of hardware support for logical partitioning, such ashardware registers which hold state information. E.g., from a hardwarestandpoint, there is nothing which prevents a task executing inpartition A from writing to an I/O device in partition B. Low levellicensed internal code function and/or hardware prevent access to theresources in other partitions.

Code enforcement of logical partitioning constraints means that it ispossible to alter the logical configuration of a logically partitionedcomputer system, i.e., to change the number of logical partitions orre-assign resources to different partitions, without reconfiguringhardware. Generally, a logical partition management tool is provided forthis purpose. This management tool is intended for use by a single or asmall group of authorized users, who are herein designated the systemadministrator. In the preferred embodiment described herein, thismanagement tool is referred to as the “hypervisor”. A portion of thismanagement tool used for creating or altering a configuration executesin one of the logical partitions, herein designated the “primarypartition”.

Logical partitioning of a large computer system has several potentialadvantages. As noted above, it is flexible in that reconfiguration andre-allocation of resources is easily accomplished without changinghardware. It isolates tasks or groups of tasks, helping to prevent anyone task or group of tasks from monopolizing system resources. Itfacilitates the regulation of resources provided to particular users;this is important where the computer system is owned by a serviceprovider which provides computer service to different users on afee-per-resource-used basis. Finally, it makes it possible for a singlecomputer system to concurrently support multiple operating systems,since each logical partition can be executing in a different operatingsystem.

Additional background information regarding logical partitioning can befound in the following commonly owned patents and patent applications,which are herein incorporated by reference: Ser. No. 09/838,057, filedApr. 19, 2001, entitled Method and Apparatus for Allocating ProcessorResources in a Logically Partitioned Computer System; U.S. Pat. No.6,766,398 to Holm, et al.; U.S. Pat. No. 6,820,164 to Holm et al.; U.S.Pat. No. 6,662,242 to Holm et al.; Ser. No. 09/672,043, filed Sep. 29,2000, entitled Technique for Configuring Processors in System WithLogical Partitions; U.S. Pat. No. 6,438,371 to Doing et al; U.S. Pat.No. 6,467,007 to Armstrong et al.; U.S. Pat. No. 6,681,240 to Armstronget al.; Ser. No. 09/314,324, filed May 19, 1999, entitled Management ofa Concurrent Use License in a Logically Partitioned Computer; U.S. Pat.No. 6,691,146 to Armstrong et al.; U.S. Pat. No. 6,279,046 to Armstronget al.; U.S. Pat. No. 5,659,786 to George et al.; and U.S. Pat. No.4,843,541 to Bean et al. The latter two patents describe implementationsusing the IBM S/360, S/370, S/390 and related architectures, while theremaining patents and applications describe implementations using theIBM AS/400 and related architectures.

DETAILED DESCRIPTION

The major hardware components of a multiprocessor computer system 100for utilizing a query optimizing technique according to the preferredembodiment of the present invention are shown in FIG. 1. Multiplecentral processing units (CPUs) 101A-101H concurrently perform basicmachine processing function on instructions and data from main memory102. Each processor preferably contains or controls a respective cache.These cache structures are shown conceptually in FIG. 1 as a singleblock 106A-106H for each respective processor; however, it should beunderstood that a processor's cache may include multiple separatestructures at multiple levels, such as an on-chip L1 instruction cache,an on-chip L1 data cache, an on-chip L2 cache directory/controller, andan L2 cache memory on a separate chip. For purposes of this invention,the precise implementation details of caching in each processor are notsignificant, and the caches could be implemented differently, or theinvention could be implemented without caches associated with theprocessors.

A pair of memory buses 103A, 103B connect the various CPUs, main memory,and I/O bus interface unit 105. I/O bus interface unit 105 communicateswith multiple I/O processing units (IOPs) 111-117 through respectivesystem I/O buses 110A, 110B. In the preferred embodiment, each systemI/O bus is an industry standard PCI bus. The IOPs support communicationwith a variety of storage and I/O devices, such as direct access storagedevices (DASD), tape drives, workstations, printers, and remotecommunications lines for communication with remote devices or othercomputer systems. While eight CPUs, two memory buses, two I/O buses, andvarious numbers of IOPs and other devices are shown in FIG. 1, it shouldbe understood that FIG. 1 is intended only as an illustration of thepossible types of devices that may be supported, and the actual numberand configuration of CPUs, buses, and various other units may vary. Itshould also be understood that the buses are illustrated in a simplifiedform as providing communications paths between various devices, and infact the actual bus structure may be more complex, and containadditional hierarchies or components not shown. For simplicity, CPUs,memory buses and I/O buses are herein designated generically byreference numbers 101, 103 and 110, respectively.

While various system components have been described and shown at a highlevel, it should be understood that a typical computer system containsmany other components not shown, which are not essential to anunderstanding of the present invention. In the preferred embodiment,computer system 100 is a multiprocessor computer system based on the IBMAS/400 or I/Series architecture, it being understood that the presentinvention could be implemented on other multiprocessor computer systems.

FIG. 2 is a conceptual illustration showing the existence of logicalpartitions at different hardware and software levels of abstraction incomputer system 100. FIG. 2 represents a system having four logicalpartitions, it being understood that the number of partitions may vary.As is well known, a computer system is a sequential state machine whichperforms processes. These processes can be represented at varying levelsof abstraction. At a high level of abstraction, a user specifies aprocess and input, and receives an output. As one progresses to lowerlevels, one finds that these processes are sequences of instructions insome programming language, which continuing lower are translated intolower level instruction sequences, and pass through licensed internalcode and ultimately to data bits which get put in machine registers toforce certain actions. At a very low level, changing electricalpotentials cause various transistors to turn on and off. In FIG. 2, the“higher” levels of abstraction are represented toward the top of thefigure, while lower levels are represented toward the bottom.

As shown in FIG. 2 and explained earlier, logical partitioning is acode-enforced concept. At the hardware level 201, logical partitioningdoes not exist. As used herein, hardware level 201 represents thecollection of physical devices (as opposed to data stored in devices),such as processors, memory, buses, I/O devices, etc., shown in FIG. 1,including other hardware not shown in FIG. 1. As far as a processor 101is concerned, it is merely executing machine language instructions. Inthe preferred embodiment, each processor is identical and more or lessinterchangeable. While code can direct tasks in certain partitions toexecute on certain processors, there is nothing in the processor itselfwhich dictates this assignment, and in fact the assignment can bechanged by the code. Therefore the hardware level is represented in FIG.2 as a single entity 201, which does not distinguish between logicalpartitions.

Immediately above the hardware is a common low-level hypervisor base202, also called partitioning licensed internal code (PLIC), whichenforces logical partitioning. As represented in FIG. 2, there is nodirect path between higher levels (levels above hypervisor 202) andhardware level 201, meaning that commands or instructions generated athigher levels must pass through hypervisor 202 before execution on thehardware. Hypervisor 202 enforces logical partitioning of processorresources by presenting a partitioned view of hardware to the taskdispatchers at higher levels. I.e., task dispatchers at a higher level(the OS kernel) dispatch tasks to virtual processors defined by thelogical partitioning parameters, and the hypervisor in turn dispatchesvirtual processors to physical processors at the hardware level 201 forexecution of the underlying task. The hypervisor also enforcespartitioning of other resources, such as allocations of memory topartitions, and routing I/O to I/O devices associated with the properpartition. Hypervisor 202 contains state data, some of which may bestored in special purpose registers while other such state data isstored in tables or other structures. Essentially, this state datadefines the allocation of resources in logical partitions, and theallocation is altered by changing the state data rather than by physicalreconfiguration of hardware.

Above hypervisor 202 is another level of machine management code hereinidentified as the “OS kernel” 204A-204D. At the level of the OS kernel,each partition behaves differently, and therefore FIG. 2 represents theOS Kernel as four different entities 204A-204D corresponding to the fourdifferent partitions. In general, each OS kernel 204A-204D performsroughly equivalent functions, and the OS kernel is herein genericallyreferred to as feature 204. However, it is not necessarily true that allOS kernel 204A-204D are identical copies of licensed internal code, andthey could be different versions of architecturally equivalent licensedinternal code, or could even be architecturally different licensedinternal code modules. OS kernel 204 performs a variety of taskmanagement functions, and in particular, enforces data integrity andsecurity among multiple tasks.

Above the OS kernel are a set of high-level operating system functions205A-205D, and user application code and data 206A-206D. A user maycreate code in levels 206A-206D which invokes one of high leveloperating system functions 205A-205D to access the OS kernel, or maydirectly access the OS kernel. This is represented in FIG. 2 by showingthat both high level operating system functions 205A-205D and userapplication levels 206A-206D reach the OS kernel boundary. In the AS/400architecture, a user-accessible architecturally fixed “machineinterface” 210 forms the upper boundary of the OS kernel, (the OS kernelbeing referred to as “SLIC”), but it should be understood that differentoperating system architectures may define this interface differently,and that it would be possible to operate different operating systems ona common hardware platform using logical partitioning.

One and only one of the logical partitions is designated the primarypartition, which is the partition used by the system administrator tomanage logical partitioning. The primary partition contains a specialportion of hypervisor code 203 which shares the level of OS kernel 204A.Hypervisor portion 203 contains code necessary to create or alterlogical partition definitions. Collectively, hypervisor portion 203 andhypervisor base 202 constitute the hypervisor. Additionally, auser-to-hypervisor interface 208 is provided at the OS kernel level inthe primary partition. Interface 208 provides functions for interactingwith a user (system administrator) to obtain user-specified partitioningparameters. The functions available in interface 208 may be useddirectly in a direct-attach terminal, or may be accessed through a setof APIs from other interface code (not shown) in any device (such as anintelligent workstation) connected to computer system 100. Thehypervisor is super-privileged code which is capable of accessingresources, and specifically processor resources, in any partition. Thehypervisor causes state values to be written to various hardwareregisters and other structures, which define the boundaries and behaviorof the logical partitions.

In accordance with the preferred embodiment, the administrator definesmultiple logical partitions and the resources available to each. Withrespect to processing resource, the administrator specifies four things:the number of virtual processors available to each partition, theprocessing capacity available to the partition, whether the assignedprocessing capacity is capped, and the assignment of physical processorsto partitions. The processor parameters are explained with reference tothe examples below. Any or all of these parameters may be dynamicallychanged by the administrator, effecting an altered configuration. By“dynamically changed” it is meant that the administrator may altercertain parameters which define a logical partition while the computersystem is operating, without the need to shut down the system andre-initialize it. It is not necessarily the case that all parameterswhich define logical partitions may be altered dynamically, but in thepreferred embodiment, the processor parameters described herein can bedynamically altered. One consequence of the capability to dynamicallychange the logical partition defining parameters is that a job orprocess may commence execution in a logical partition P having definedparameters p₁, p₂, p₃ . . . , and while the job or process is executingthese parameters may change to p₁′, p₂′, p₃′ . . . , so that the job orprocess continues executing in partition P, having differentcharacteristics.

FIG. 3 shows an example logical partitioning processor allocation for asystem having eight physical processors. As shown in FIG. 3, fourlogical partitions 301-304 are defined. For each logical partition,there exists a respective virtual processor assignment 310, and aprocessing capacity allocation 311. Additionally, there exists anallocation 312 for physical processors. In the example of FIG. 3,logical partition 301 is assigned one virtual processor and 0.5processing unit of processing capacity; logical partition 302 isassigned four virtual processors and 3.5 processing units of processingcapacity; and partition 303 is assigned two virtual processors and 1.0unit of processing capacity. Partition 304 is assigned three dedicatedprocessors (an actual processing capacity of 3.0 units). Virtualprocessors are always assigned in integer numbers. Processing capacityis not necessarily an integer.

In the example of FIG. 3, two sets of processors 315, 316 are defined.Set 315, which is a “pool”, contains five physical processors, while set316 contains three. Logical partitions 301-303 execute in pool 315,while partition 304 executes in set 316.

A physical processor allocation constrains a task executing in anassociated partition to run on only the processors allocated to theprocessor set to which the partition is assigned. In this embodiment, aset of one or more processors may be assigned to a partition indedicated mode, or may be assigned to a processor pool, to which one ormore partitions are in turn assigned. Dedicated mode means simply thatthe full capacity of the set of physical processors is dedicated to asingle partition. In a pooled mode, the processors are assigned to apool, which is typically (although not necessarily) shared among morethan one partition. Dedicated mode is functionally equivalent to a poolto which only one logical partition is assigned, and in which the fullcapacity and number of virtual processors of the pool are given to theone partition.

Thus, in the example of FIG. 3, set 315 is shared among multiplepartitions and is a processor pool, while set 316 is a set of processorsdedicated to partition 304. A task executing in partition 301 can bedispatched to any of the five physical processors allocated to pool 315,but can not be dispatched to any of the three physical processorsallocated to set 316, even if those processors are idle. Since pool 315is shared among partitions 301-303, the tasks executing in thesepartitions share the five processors assigned to pool 315.

The processing capacity allocation specifies the amount of equivalentprocessing power allocated to a partition in processor units. I.e., oneprocessor unit is the equivalent of a single physical processorexecuting 100% of the time. The sum of the processing capacityallocations of all partitions assigned to a particular processor poolcan not exceed the number of physical processors in the pool, althoughit may be less than the number of physical processors in the pool (inwhich case, there is unallocated processor capacity).

In the example of FIG. 3, logical partition 301 is allocated 0.5 unitsof processing capacity, which means it is allocated a capacityequivalent to one physical processor executing 50% of the time (orrunning at 50% of normal speed). However, this does not mean that one ofthe processors in pool 315 will execute roughly half time on behalf oftasks in partition 301. Work from any one partition assigned to a poolis distributed among the processors in the pool, and it can be expectedthat on the average each of the five processors in pool 315 will devoteabout 10% of its capacity to executing on behalf of tasks from partition301. The user specifies a processing capacity allocation only forpartitions assigned to pools; partitions having dedicated processorsautomatically receive the full capacity of the dedicated processors.FIG. 3 therefore shows a processing capacity of 3.0 for partition 304,this being an equivalent number, although in fact the user does notspecify a processing capacity.

The virtual processor assignment specifies the number of virtualprocessors seen by each respective partition which is assigned to a poolof processors. To the partition, the underlying hardware and dispatchingcode behaves like the number of virtual processors specified, each ofwhich is running at some fraction of the power of a single physicalprocessor, the fraction being the number of virtual processors dividedby the number processing units allocated to the partition. Thus, in theexample of FIG. 3, partition 302 sees four virtual processors, eachoperating at approximately 82.5% (3.5/4) of the capacity of a singlephysical processor. Partition 303 sees two virtual processors, eachoperating at 50% of the capacity of a single physical processor. Likeprocessing capacity, the user specifies a virtual processor allocationonly for partitions assigned to pools; partitions having dedicatedprocessors automatically receive a number of virtual processors equal tophysical processors. FIG. 3 therefore shows three virtual processors forpartition 304.

A logical partition assigned to a pool may be designated either cappedor uncapped. A capped partition can not use more processing capacitythan its allocation, even if processors are idle due to lack ofavailable work from other partitions in the same pool. Capping assuresthat a particular logical partition will not exceed its allocated usage,which is desirable in some circumstances. An uncapped partition mayutilize spare processing capability beyond its allocation, provided thatit may not execute its tasks on physical processors outside its assignedprocessor pool. Capping does not apply to partitions having dedicatedprocessors.

The configuration of FIG. 3 is merely a single example configuration,and many variations are possible. The number of processor sets may vary.Since sets of processors are disjoint and each set must have at leastone physical processor, the number of such sets is necessarily limitedby the number of physical processors in the system. But in otherrespects, the administrator is free to allocate sets as he wishes, andmay allocate zero, one or multiple sets which are pools, and zero, oneor multiple sets which are dedicated to a single respective logicalpartition. Additionally, while a processor pool is usually used forsharing among multiple partitions, a processor pool could have only asingle partition assigned to it. For example, if for some reason it isdesired to limit the processor resources allocated to a single logicalpartition, a pool containing a single processor could be defined, towhich a single logical partition is assigned, the partition being givena processing capacity of 0.5 processors and specified as capped. Itshould further be understood that the set of processor parametersdescribed above which are associated with logical partitions are simplyone implementation of the general concept of logical partitioning, andthat different parameters could be used to define the characteristics ofeach logical partition.

Each user job or process is assigned to a respective logical partition.Typically, a single logical partition will contain many userapplications (although some partitions may be dedicated to specialpurposes). FIG. 4 illustrates at a high level various user applicationsand data in a logical partition of computer system 100.

As shown in FIG. 4, at a level above machine interface 210 in a logicalpartition P, there exists high level operating system functions 205 anduser applications and data 206. Database management system 401 providesbasic functions for the management of user databases. Databasemanagement system 401 may theoretically support an arbitrary number ofdatabases, but only a single database 410 is illustrated in FIG. 4. Inaddition to database management system 401, other user applications404-405 may execute in partition P. Such other user applications mayinclude, e.g., word processing, accounting, code development andcompilation, mail, calendaring, or any of thousands of userapplications. Some of these applications may access data in database410, while others may not.

Database 410 is illustrated in FIG. 4 as a conceptual entity becausevarious applications at this level may access it. However, it will beunderstood that the database itself is not executable code and does notitself perform a function. Database 410 may be extremely large, andcould include data on other systems which is accessed through remoteprocedure calls or the like.

Database management system 401 preferably supports a variety of databaserelated functions. Specifically, it allows users to perform basicdatabase operations, such as defining a database, altering thedefinition of the database, creating, editing and removing records inthe database, viewing records in the database, and so forth. It mayfurther contain any of various more advanced database functions.Database management system 401 may be contained entirely withinhigh-level operating system 205, or may be separate from high-level OS205, or portions of it may be within high-level OS 205 while otherportions are separate.

Among the functions supported by database management system 401 is themaking of queries against data in database 410. As is known, queriestypically take the form of statements having a defined format, whichtest records in the database to find matches to some set of logicalconditions. Typically, multiple conditions are connected by logicalconjunctives such as “AND” and “OR”. Because database 410 may be verylarge, having a very large number of records, and a query may be quitecomplex, involving multiple logical conditions, it can take some timefor a query to be executed against the database, i.e., for all thenecessary records to be reviewed and to determine which records, if any,match the conditions of the query.

The amount of time required to perform a complex query on a largedatabase can vary greatly, depending on many factors. Depending on howthe data is organized and indexed, and the conditions of the query, itmay be desirable to evaluate records in a particular order, to evaluatecertain logical conditions before evaluating other logical conditions,to evaluate certain logical conditions in parallel, and/or to evaluateconditions against subsets of the database in parallel.

In order to provide improved database query support, database managementsystem 401 contains query optimizer portion 402. Optimizer 402 generatessearch strategies for performing database queries. A search strategy isa defined series of steps for performing the query, and thus is, ineffect, a computer program. The optimizer 402 which generates the searchstrategy is something akin to a compiler, although the strategy is notnecessarily executable level code, and is more typically a higher-levelseries of statements which invoke low-level operating system functions.Once created by optimizer 402, a strategy is saved as a persistentstorage object in memory and can be written to disk or other storage. Ittherefore can be executed many times. Persistent storage objects labeled“Query A” 411 and “Query B” 412 in FIG. 4 represent query strategiesgenerated by optimizer 402. These objects are “persistent” in the sensethat they exist independently of the user process under which they werecreated, and may continue to reside in memory or disk storagenotwithstanding that the user process has terminated. Although these arereferred to herein as “query strategy objects”, the use of the term“object” is not meant to imply that database management system 401 orthe user application are necessarily programmed using so-calledobject-oriented programming techniques, or that the “query strategyobject” necessarily has the attributes of an object in anobject-oriented programming environment, although it would be possibleto implement them using object-oriented programming constructs.

FIG. 5 is a flow diagram illustrating at a high level the process ofgenerating an optimized query strategy object 411, 412. The userinitially creates a source query using any of various tools available(step 501). Preferably, database management system 401 contains aninteractive query generation and editing function as is known in theart, which allows the user to interactively specify the logicalconditions of the query. However, a query could be generated using atool external to database management system 401. For example, somedatabase management systems support queries in plain text, which couldbe generated with any text editor. The query could be created in any ofvarious database query languages, now known or hereafter developed, suchas SQL. The source query may be saved to disk storage, and re-editedmultiple times, so that there may be a considerable gap in time betweenstep 501 and the remaining steps of FIG. 5.

After generating the source query, the user application passes thesource to the database management system 401, which calls the queryoptimizer 402 to create an optimized query strategy for executing thesource query (step 502). Depending on the sophistication of the queryoptimizer, there may be various user selectable parameters which can beset to regulate the optimization. For example, the user may specifywhether the query is to be optimized to rapidly produce partial results(which may mean that a less than optimal process for producing fullresults is used), or optimized to produce full results (which may meanthat partial results are not available as soon as possible).

The query optimizer determines the system configuration to which thequery will be optimized (step 503). Various system configurationparameters may be used, some of which may be fixed (such as a type orclock speed of processor), while others are variable depending on alogical partition definition. Specifically, in the preferred embodiment,one of the system configuration parameters is the number of virtualprocessors, which is a characteristic of a logical partition subject todynamic alteration. The number of virtual processors in effect specifiesthe degree of parallelism allowed for query execution, and may thereforeaffect the strategy chosen for query execution. It would be possible touse other or additional logical configuration parameters in determiningan optimum strategy. For example, as one alternative embodiment, theoptimizer additionally uses the logical process sing capacity of thepartition. This information may be significant, e.g., where the user hasspecified a time limit for query execution.

In the preferred embodiment, the logical partition parameters used bythe query optimizer are the parameters associated with the logicalpartition in which the query optimizer is executing, and at the time thequery optimizer generates the optimized query. However, the logicalpartition parameters for which a query is optimized need not be limitedto any particular logical partition. In an alternative embodiment, theuser could specify an arbitrary set of logical partition parameters foruse in optimizing a query.

The query optimizer parses the source query to generate a logical queryrepresentation (step 504). In some environments, the step of parsing maybe performed by a separate application before calling the optimizer, anda parsed version of the query may be saved as a file in someintermediate representation. Therefore, step 504 is not necessarilyperformed after steps 502 or 503.

With the source query parsed and the optimization parameters determined,the optimizer then generates an optimized query strategy according tothe specified parameters (step 505). This optimized query strategy isoutput as a query strategy object 411, 412, which may be saved to disk,and which may be executed multiple times and at spaced-apart intervals.Additionally, it is possible that the query strategy may be laterexecuted in a logical partition other than the partition in which theoptimizer was executing when the strategy was generated. Query strategyobject 411, 412 contains, in addition to the query execution strategy,the various input parameters which were used to generate the query, andin particular, the logical partition processor configuration parameters.

FIG. 6 is a flow diagram illustrating at a high level the process ofexecuting a previously optimized query strategy. A query is firstcreated and a query strategy generated as described above with respectto FIG. 5. The user invokes the database management system, which loadsthe query strategy object into memory (step 601). If the strategy objectis already in memory (e.g., the strategy is to be executed immediatelyafter optimization as described above), then step 601 is not required.The user invokes the query for execution, specifying any desiredexecution parameters (step 602). The database management system 401 maysupport various execution parameters which are invoked when the query iscalled for execution, and which control the execution of the query.

In the preferred embodiment, the user may specify whether the query isto be re-optimized if there has been a change in logical partitionparameters. By default, it is assumed that the query should bere-optimized if the configuration has changed. However, the user maywish to override this default, and may do so as an execution parameterwhen the query is invoked. E.g., the user may know that the query willbe run only once with the current configuration, and may simply wish toavoid spending time in re-optimization. Alternatively, the user may wishto maintain the same query strategy because it has known performancecharacteristics. In an alternative embodiment, the query is alwaysre-optimized upon a configuration change.

Upon receiving the user command to invoke the query, the databasemanagement system 401 retrieves the current configuration of the logicalpartition in which the query will execute (step 603). The databasemanagement system determines whether the query is to be re-optimized ona change in configuration of the logical partition parameters (step604), i.e., whether the user has overridden the default to re-optimize.If the default has not been overridden, the “Y” branch is taken fromstep 604. The database management system therefore compares the logicalpartition configuration assumptions under which the optimizer originallygenerated the query strategy and which are stored in the query strategyobject, with the current configuration of the logical partition in whichthe query will execute (step 605).

If the configuration has changed, the “Y” branch is taken from step 605.In this case, the optimizer is automatically called to generate a newconfiguration strategy according to the current logical partitionconfiguration (step 606). I.e., either the original query source file orsome parsed representation thereof is retrieved; the optimizer isinvoked using the same optimization parameters as were used originally,except that the current logical partition configuration is used in placeof the original parameters, and the optimizer generates a new querystrategy object. In the preferred embodiment, the optimizer simplyre-optimizes the query using the original parameters except forconfiguration; however, it would alternatively be possible to solicituser interactive input to vary any of the query optimization parameters,even those unrelated to logical partition configuration. The newlygenerated query strategy may either be a contained in a separate objectin addition to the original query strategy object, or may replace theoriginal query strategy object.

The system then executes the query strategy (step 607), which is eitherthe original query strategy if step 606 has not been taken, or there-optimized query strategy if step 606 has been taken.

A particular set of logical partition parameters has been described inthe preferred embodiment, and a particular parameter (i.e., virtualprocessors) used by the optimizer to generate an appropriate querystrategy. However, it will be appreciated that a logically partitionedcomputer system could use other configuration parameters; that otherparameters (including parameters described herein as well as those notdescribed) may affect an optimization strategy for a query; and that aquery optimizer could use these other parameters in addition to or inplace of the parameters described herein.

In general, the routines executed to implement the illustratedembodiments of the invention, whether implemented as part of anoperating system or a specific application, program, object, module orsequence of instructions may be referred to herein as “computerprograms” or simply “program”. The computer programs typically compriseinstructions which, when read and executed by one or more processors inthe devices or systems in a computer system consistent with theinvention, cause those devices or systems to perform the steps necessaryto execute steps or generate elements embodying the various aspects ofthe present invention. Moreover, while the invention has and hereinafterwill be described in the context of fully functioning computer systems,the various embodiments of the invention are capable of beingdistributed as a program product in a variety of forms, and theinvention applies equally regardless of the particular type ofsignal-bearing media used to actually carry out the distribution.Examples of signal-bearing media include, but are not limited to,recordable type media such as volatile and non-volatile memory devices,floppy disks, hard-disk drives, CD-ROM's, DVD's, magnetic tape, andtransmission-type media such as digital and analog communications links,including wireless communications links. Examples of signal-bearingmedia are illustrated in FIG. 1 as main memory 102 and as storagedevices attached to storage IOPs 111, 112 and 116.

In the preferred embodiment described above, the computer systemutilizes an IBM AS/400 or I/Series architecture. It will be understoodthat certain implementation details above described are specific to thisarchitecture, and that logical partitioning management mechanisms inaccordance with the present invention may be implemented on differentarchitectures, and certain implementation details may vary.

While the invention has been described in connection with what iscurrently considered the most practical and preferred embodiments, it isto be understood that the invention is not limited to the disclosedembodiments, but on the contrary, is intended to cover variousmodifications and equivalent arrangements included within the spirit andscope of the appended claims.

1. A computer system, comprising: a plurality of central processingunits; a memory; a logical partitioning mechanism supporting a pluralityof defined logical partitions of said computer system, each logicalpartition having a respective processor resource assignment, whereineach task executing in said computer system is assigned to a respectiveone of said logical partitions and restricted to using only theprocessor resources which are allocated to the respective logicalpartition by its respective processor resource assignment, and whereinthe definition of said logical partitions may be dynamically altered; adatabase; a database management system for managing said database,wherein said database management system: (a) performs query optimizationof a database query for said database to produce a first searchstrategy, said first search strategy being dependent on a firstprocessor resource assignment; (b) responsive to invoking said firstquery search strategy for execution, compares said first processorresource assignment with a second processor resource assignmentassociated with a logical partition of execution at the time said firstsearch strategy is invoked for execution; and (c) depending on theresults of said comparison performed in (b), automatically constructs asecond search strategy dependent on said second processor resourceassignment; wherein said first processor resource assignment is theprocessor resource assignment for a logical partition with which saiddatabase query is associated at the time said database management systemperforms query optimization of said database query for said database toproduce said first search strategy, said database management systemautomatically determining said processor resource assignment for saidlogical partition with which said database query is associated.
 2. Thecomputer system of claim 1, wherein said respective processor resourceassignment of each partition comprises a respective number of virtualprocessors of each partition, said respective number being an integer.3. The computer system of claim 2, wherein said logical partitioningmechanism supports the definition of at least one set of processorswhich is shared by a set of said logical partitions, said set of saidlogical partitions containing at least two partitions, said respectiveprocessor resource assignment of each partition of said set ofpartitions including said set of processors.
 4. The computer system ofclaim 1, wherein said database management system saves said first searchstrategy in a persistent object for later execution, said persistentobject including said first processor resource assignment.